HandWave is an innovative real-time hand sign detection application designed to bridge the communication gap between the hearing and speech-impaired community and the rest of the world. By leveraging computer vision and machine learning, HandWave converts sign language gestures into text and voice, fostering inclusivity and accessibility.
🚀 High Accuracy: Achieves 99% accuracy in dynamic environments.
📊 Extensive Dataset: Trained on a custom dataset of 77,000 samples across 32 distinct hand sign classes.
⚡ Real-Time Processing: Utilizes Mediapipe for rapid hand landmark detection and a Random Forest model for gesture classification.
🔊 Text-to-Speech Integration: Converts recognized hand signs into audible speech for enhanced communication.
🖥️ User-Friendly Interface: Simple design allowing seamless interaction through webcam input.
🏗️ Model Architecture: Combines Mediapipe’s hand tracking capabilities with a Random Forest classifier, providing efficient and accurate recognition.
🗂️ Data Collection: Manually curated dataset encompassing 32 hand sign classes with variations in angle, lighting, and background.
🗣️ Speech Synthesis: Uses advanced speech synthesis software to convert detected text into audio, ensuring smooth interaction.
🧑💻 Deployment: Lightweight and optimized for real-time deployment on consumer-grade hardware.
🧏 Accessibility Tools: Assists hearing and speech-impaired individuals in daily communication.
📚 Educational Aid: Supports learning and teaching sign language through interactive feedback.
🏥 Healthcare: Facilitates communication in medical environments where verbal interaction may not be possible.
🏢 Customer Service: Empowers businesses to offer inclusive communication channels.
🔄 Expansion to detect full sentence gestures.
🌍 Support for additional sign languages across regions.
📱 Integration with mobile devices for wider accessibility.
HandWave exemplifies the potential of technology to create inclusive solutions that break down barriers and promote equality. If you like my project, Please do give it a try by going to my Github!!
